Magistrate Judge Andrew Peck of the U.S. District Court in the Southern District of New York opined in his Feb. 24 decision that defendants could use predictive coding, a software tool that uses algorithms to automatically tag documents, to review as many as 3 million electronic documents as part of the parties’ e-discovery protocol. Because the plaintiffs and defendants both agreed to use predictive coding to cull from the massive number of documents, the case serendipitously allowed Judge Peck, who is a well-known e-discovery technology advocate, a chance to plant his flag and advance the field.

Although many technology vendors may point to Judge Peck’s opinion as a validation of predictive coding as a judicially endorsed product, this is not necessarily the case.

“This opinion provided him with a way to make his ‘Search, Forward’ article (that offered tentative, circumstantial judicial approval of predictive coding) more official,” says James Hanft, counsel at Schiff Hardin. “This doesn’t have that much legal weight to it because both parties agreed to it. It simply gives insights into what [Judge Peck] and a lot of other judges are thinking in respect to the acceptability of computer-assisted coding.”

Getting Transparency

What Judge Peck does say in his opinion is that predictive coding is an appropriate tool in certain cases, but only if it is part of a defensible process that is subjected to the same quality-control testing appropriate to any type of document review.

“Judges don’t want you to be perfect,” explains Cozen O’Connor Member Dave Walton, “they want you to be reasonable. Using predictive coding—if it’s been tested and sampled, there is more-than-adequate research behind it to show that it’s reasonable. But that still doesn’t mean predictive coding is good for every type of case.”

Another important point in Judge Peck’s opinion that may have been lost in the furor is the issue of transparency. He wrote that he granted the defendant’s e-discovery protocol, in part, because it was willing to be fully transparent with the plaintiffs and show them the results of the sampling as well as the results of the metrics to ensure nothing was missing.

“If you show you’ve got nothing to hide, a judge is going to give you the benefit of the doubt if you’re trying to employ creative means and tools to reduce the ESI blob,” Walton says.

Despite the transparency, however, as of press time, there are still unresolved issues. The plaintiffs have appealed Judge Peck’s ruling to U.S. District Judge Andrew Carter for the final dispensation of the predictive coding workflow, alleging Peck didn’t give them time to address his ruling, and that he expanded the reasoning of his ruling after they filed their objections. And some of these questions are likely to be inherent to most cases involving predictive coding.

“The discussion around the disagreement about the approaches and the best way to put the technology to use is an important one,” says Mikki Tomlinson, director of the strategic consulting services division for EDJ Group. “There are multiple disagreements that are being played out: How big should the sample sizes be? At what point should you stop? At what point are the parties going to call system trained? How is it being validated?”

Of course, questions like these will always be present and will vary on a case-by-case basis. But given time and experience using predictive coding, parties eventually will become more accustomed to it, and getting those answers will become easier.

Predicting Use

Judge Peck’s opinion raises the question: When is the use of predictive coding appropriate? Experts agree that right now, given the high cost of the technology, it’s best used in cases with a significant amount of data to warrant that cost. Also necessary at the moment is a large enough set of responsive documents within the data collection to allow the software to be effective. Vendors, however, are working on adapting their tools to make predictive coding more appropriate for smaller cases.

“What predictive coding is really going to do is replace the army of contract lawyers that are out there reviewing the documents,” Walton says.

Another point to consider is that, for predictive coding to be effective, documents need to be in a form that the program can easily parse. Large document sets that are PDFs will need to be converted to a machine-readable form before being reviewed, which can create problems given the conversion accuracy of optical character recognition programs. Similar issues occur with handwritten notes, drawings and other non-email documents.

There also can be problems with words, word association or pattern recognition. Attorneys see case after case with the same words used over and over, inherently know context and can read between the lines. Predictive coding, as effective as it is, cannot always find those same patterns.

“[With predictive coding,] you’re going to miss the one-off thing where someone may use different word patterns or different words to say the same thing,” Hanft says.

Up to Code

At the moment, there’s still more smoke than fire when it comes to predictive coding. It’s exciting and buzzed about, but not a lot of companies or law firms are regularly using it.

“It’s definitely being used,” says Symantec Corp. Senior eDiscovery Counsel Dean Gonsowski, “but it’s kind of a Ph.D.-level-use case right now. The workflows, the processes and the understanding of how a traditional workflow comes into play when you get to predictive coding are magnified. It has a place, but you’ve got to get your graduate degree first, otherwise you’re going to have litigators’ heads exploding.”

Until those issues are solved, or at least better ironed out, mainstream adoption of predictive coding will remain limited. Gonsowski believes that 2012 is the year for awareness and experimentation, and forward-thinking attorneys will start trying a few cases using the technology. By next year, he predicts, some of the transparency issues will have gone away, a workflow will have been established, and case law will have developed for attorneys to use predictive coding with greater regularity.